Images and videos are stored and communicated to an increasing extent by contemporary human population, for example multimedia content via Internet and wireless communication networks. The images and videos are stored and communicated between devices, software applications, media systems and data services. During such storage and communication, images and video are captured scanned, transmitted, shared, watched and printed. However, such images and videos are demanding in respect of data memory capacity and communication system bandwidth utilized. When communication system bandwidth is limited, such images and videos take significant time to communicate. For addressing such storage requirements, it has been customary practice to employ image and video encoding methods which also provide a degree of data compression. Some contemporary encoding standards for images and video are provided in Table 1.
TABLE 1contemporary encoding standardsJPEGMPEG-1H.261WebPLucidJPEG2000MPEG-2H.263WebMGIFJPEG XRMPEG-4H.264PNGMPEG-4 AVCTIFFMPEG-4 MVCBMPMP3VC-1TheoraAACFLACOgg VorbisSpeex
Image and audio files are becoming larger as image quality is progressively improved, for example by adoption of high definition (HD) standards and high dynamic range (HDR). However, 3-dimensional (3-D) images, videos and audio are gaining increasing popularity which demands correspondingly more efficient encoding and decoding methods in encoders and decoders, namely “codecs”, to cope with associated increased quantities of data to be communicated and stored. However, it is highly desirable that encoding methods that provide a degree of data compression should be substantially lossless in relation to information content when generating the compressed data.
Conventional codecs are described in earlier published patent applications and granted patents, for example as in US5832130, US7379496 and US7676101. In general, known video codecs are not able to code efficiently extensive areas of images with substantially constant parameters whilst concurrently being able to encode highly spatially detailed areas of the images. It is customary practice to employ motion compensation in a form of prediction and prediction error coding methods based upon use of transformations, for example discrete cosine transform (DCT) and wavelet transformations. These transformations employ a process wherein portions of a given image, for example a still image or an image forming a part of a video sequence, are divided into blocks which are then subject to encoding processes. The blocks are, for example, 8×8 image elements, 4×4 image elements or similar. Such relatively smaller blocks are employed because larger sizes of blocks result in inefficient encoding processes, although 16×16 image element blocks are sometimes employed. According to contemporary known approaches to image encoding, when multiple different block sizes are used for encoding, it is customary practice to utilize a small variation in block sizes; moreover, block sizes are selected based upon how well movement can be compensated in an associated block area or based upon a encoding quality parameter, for example a target quality parameter. In general, higher encoded image quality requires smaller blocks which results in less data compression. Certain types of contemporary encoding can even results in an increase in data size, when error correction features such as parity codes and error correction codes are included.
From the foregoing, it will be appreciated that providing data compression of images and videos whilst preserving image quality is a contemporary problem which is not adequately addressed by known encoders and decoders, despite a large variety of codecs having been developed during recent decades.